The commercial broadcast industry and businesses which advertise through the RF broadcast media need to know the sizes of the audiences which are tuned to particular stations at particular times. This need has been met primarily through the use of audience participation surveys. In other words, individuals are asked, either directly or indirectly through equipment coupled to their tuners, to identify the particular stations to which they may be tuned.
The gathering of survey data through audience participation has many problems. For example, the accuracy of this data is questionable. People often feel uncomfortable about truthfully identifying broadcast programming they may be currently experiencing. With respect to radio, a majority of the listening occurs in automobiles. However, listeners cannot practically make a record, accurate or otherwise, of their listening tendencies while driving. Accordingly survey data related to listening in automobiles is particularly suspect because it is compiled from after-the-fact recollections. Furthermore, the people who agree to participate in such surveys may have different listening tendencies than others, and this factor may bias the data.
Cost represents another problem associated with gathering data through audience participation surveys. Often, expensive equipment is provided to survey participants to automatically record listening tendencies. Accuracy may improve, but a great pressure exists to keep sample sizes small to minimize the tremendous costs involved. The smaller sample sizes lead to less accurate survey data. Moreover, the use of tuner-coupled equipment is a wholly impractical alternative in surveying the automotive radio audience due to installation costs and audience reluctance to permit unneeded meddling with their automobiles. Furthermore, money is often given to survey participants to compensate them for their inconvenience. Consequently, survey data obtained through audience participation in the gathering of survey data leads to expensive data of questionable validity.
Over the years, attempts have been made at using passive electronic RF monitoring equipment to remotely identify the stations to which tuners may be tuned. Generally speaking, audiences' tuners use local oscillator signals that are related to the frequencies of the respective stations currently being tuned in. These local oscillator signals are broadcast or otherwise emitted from the tuners as very weak signals that sensitive monitoring equipment can detect.
This remote monitoring technique is desirable because it does not require cooperation from an audience, and a host of inaccuracies and costs associated with audience participation are reduced or eliminated. Large sample sizes may be monitored at low cost relative to audience participation techniques. However, prior art methodologies and systems used to implement the remote monitoring technique have proven unsuccessful.
The failure of prior art remote monitoring systems may be due, at least in part to excessive zeal in recording large sample sizes. In general, larger sample sizes are desirable because they lead to greater accuracy. However, when larger sample sizes include corrupted or otherwise unfairly skewed data, the result can easily be a less accurate survey.
Conventional remote radio monitoring systems have failed to adequately address many different situations that lead to corrupted or skewed survey data. For example, when multiple tuners are located near one other, they may be indistinguishable from one another by the monitoring equipment when they are tuned to the same station. This skews survey data in favor of less popular stations. Moreover, no standards exist for minimum local oscillator signal strength or frequency accuracy. Conventional monitoring equipment may fail to register some stations due to a weak local oscillator signal at a particular tuner and may count another station multiple times at a different tuner. In addition, background noise may cause local oscillator signals at some frequencies to be more readily detectable than at other frequencies, and this noise may skew ratings in favor of some stations at the expense of other stations. Still further, the accuracy of the survey data obtained from conventional equipment depends on the skill and concentration of human operators. This human factor infuses yet another inaccuracy into the survey data.